{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:11:15Z","timestamp":1740100275654,"version":"3.37.3"},"reference-count":31,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006754","name":"Army Research Laboratory","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006754","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,30]]},"DOI":"10.1109\/icra48506.2021.9562096","type":"proceedings-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T00:28:35Z","timestamp":1634689715000},"page":"9242-9248","source":"Crossref","is-referenced-by-count":1,"title":["MultiViewStereoNet: Fast Multi-View Stereo Depth Estimation using Incremental Viewpoint-Compensated Feature Extraction"],"prefix":"10.1109","author":[{"given":"W. Nicholas","family":"Greene","sequence":"first","affiliation":[{"name":"Massachusetts Institute of Technology,Computer Science and Artificial Intelligence Laboratory,Cambridge,MA,02139"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicholas","family":"Roy","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology,Computer Science and Artificial Intelligence Laboratory,Cambridge,MA,02139"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2975750"},{"article-title":"A more general robust loss function","year":"2017","author":"barron","key":"ref30"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00567"},{"key":"ref11","article-title":"Cascade Cost Volume for High-Resolution MultiView Stereo and Stereo Matching","author":"gu","year":"2020","journal-title":"Proc CVPR"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00260"},{"key":"ref13","article-title":"StereoNet: Guided hierarchical refinement for real-time edge-aware depth prediction","author":"khamis","year":"2018","journal-title":"Proc ECCV"},{"key":"ref14","article-title":"Spatial transformer networks","author":"jaderberg","year":"2015","journal-title":"NeurIPS"},{"key":"ref15","article-title":"Stereo processing by semiglobal matching and mutual information","author":"hirschmuller","year":"2007","journal-title":"Trans PAMI"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1023\/A:1014573219977"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298767"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.438"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.17"},{"key":"ref28","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019","journal-title":"NeurIPS"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.1999.784607"},{"key":"ref27","article-title":"Pixelwise view selection for unstructured multi-view stereo","author":"sch\u00f6nberger","year":"2016","journal-title":"Proc ECCV"},{"key":"ref3","article-title":"A space-sweep approach to true multiimage matching","author":"collins","year":"1996","journal-title":"Proc CVPR"},{"key":"ref6","article-title":"DPSNet: End-to-end Deep Plane Sweep Stereo","author":"im","year":"2019","journal-title":"Proc ICLR"},{"article-title":"Adam: A method for stochastic optimization","year":"2014","author":"kingma","key":"ref29"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008192912624"},{"key":"ref8","article-title":"MVSNet: Depth inference for unstructured multiview stereo","author":"yao","year":"2018","journal-title":"Proc ECCV"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00298"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.199"},{"key":"ref9","article-title":"PMVSNet: Learning Patch-wise Matching Confidence Aggregation for Multi-View Stereo","author":"luo","year":"2019","journal-title":"Proc ICCV"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.19"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2018.00037"},{"article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","year":"0","author":"ioffe","key":"ref22"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"journal-title":"Multiple View Geometry","year":"2003","author":"hartley","key":"ref24"},{"key":"ref23","article-title":"Group normalization","author":"wu","year":"2018","journal-title":"Proc ECCV"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.596"},{"journal-title":"Computer Vision Algorithms and Applications","year":"2010","author":"szeliski","key":"ref25"}],"event":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","start":{"date-parts":[[2021,5,30]]},"location":"Xi'an, China","end":{"date-parts":[[2021,6,5]]}},"container-title":["2021 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9560720\/9560666\/09562096.pdf?arnumber=9562096","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,2]],"date-time":"2022-08-02T23:21:45Z","timestamp":1659482505000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9562096\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,30]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/icra48506.2021.9562096","relation":{},"subject":[],"published":{"date-parts":[[2021,5,30]]}}}